# !/usr/bin/env python

# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import time

from lerobot.datasets.lerobot_dataset import LeRobotDataset
from lerobot.model.kinematics import RobotKinematics
from lerobot.processor import RobotAction, RobotObservation, RobotProcessorPipeline
from lerobot.processor.converters import (
    robot_action_observation_to_transition,
    transition_to_robot_action,
)
from lerobot.robots.so100_follower.config_so100_follower import SO100FollowerConfig
from lerobot.robots.so100_follower.robot_kinematic_processor import (
    InverseKinematicsEEToJoints,
)
from lerobot.robots.so100_follower.so100_follower import SO100Follower
from lerobot.utils.constants import ACTION
from lerobot.utils.robot_utils import precise_sleep
from lerobot.utils.utils import log_say

EPISODE_IDX = 0
HF_REPO_ID = "<hf_username>/<dataset_repo_id>"


def main():
    # Initialize the robot config
    robot_config = SO100FollowerConfig(
        port="/dev/tty.usbmodem5A460814411", id="my_awesome_follower_arm", use_degrees=True
    )

    # Initialize the robot
    robot = SO100Follower(robot_config)

    # NOTE: It is highly recommended to use the urdf in the SO-ARM100 repo: https://github.com/TheRobotStudio/SO-ARM100/blob/main/Simulation/SO101/so101_new_calib.urdf
    kinematics_solver = RobotKinematics(
        urdf_path="./SO101/so101_new_calib.urdf",
        target_frame_name="gripper_frame_link",
        joint_names=list(robot.bus.motors.keys()),
    )

    # Build pipeline to convert EE action to joints action
    robot_ee_to_joints_processor = RobotProcessorPipeline[tuple[RobotAction, RobotObservation], RobotAction](
        steps=[
            InverseKinematicsEEToJoints(
                kinematics=kinematics_solver,
                motor_names=list(robot.bus.motors.keys()),
                initial_guess_current_joints=False,  # Because replay is open loop
            ),
        ],
        to_transition=robot_action_observation_to_transition,
        to_output=transition_to_robot_action,
    )

    # Fetch the dataset to replay
    dataset = LeRobotDataset(HF_REPO_ID, episodes=[EPISODE_IDX])
    # Filter dataset to only include frames from the specified episode since episodes are chunked in dataset V3.0
    episode_frames = dataset.hf_dataset.filter(lambda x: x["episode_index"] == EPISODE_IDX)
    actions = episode_frames.select_columns(ACTION)

    # Connect to the robot
    robot.connect()

    if not robot.is_connected:
        raise ValueError("Robot is not connected!")

    print("Starting replay loop...")
    log_say(f"Replaying episode {EPISODE_IDX}")
    for idx in range(len(episode_frames)):
        t0 = time.perf_counter()

        # Get recorded action from dataset
        ee_action = {
            name: float(actions[idx][ACTION][i]) for i, name in enumerate(dataset.features[ACTION]["names"])
        }

        # Get robot observation
        robot_obs = robot.get_observation()

        # Dataset EE -> robot joints
        joint_action = robot_ee_to_joints_processor((ee_action, robot_obs))

        # Send action to robot
        _ = robot.send_action(joint_action)

        precise_sleep(1.0 / dataset.fps - (time.perf_counter() - t0))

    # Clean up
    robot.disconnect()


if __name__ == "__main__":
    main()
